According to the hypothesis in [1]} and ablation in the previous part, the initialization has a large influence on the final network.
Since we use the same initialization in the student learning phase, the training process will tend to a specific result which can be represented with a static transformation.
From this perspective, a static transformation has the ability to match the features well.
As a result, it's unnecessary to use a dynamic transformation.
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